Global analysis of condition-specific subcellular protein distribution and abundance

Transcriptome Analysis of the Influence of High-Pressure Carbon Dioxide on Saccharomyces cerevisiae under Sub-Lethal Condition

High-pressure carbon dioxide (HPCD), a novel non-thermal pasteurization technology, has attracted the attention of scientists due to its high pasteurization efficiency at a lower temperature and pressure. However, the inactivation mechanism has not been well researched, and this has hindered its commercial application. In this work, we used a sub-lethal HPCD condition (4.0 MPa, 30 °C) and a recovery condition (30 °C) to repair the damaged cells. Transcriptome analysis was performed by using RNA sequencing and gene ontology analysis to investigate the detailed lethal mechanism caused by HPCD treatment. RT-qPCR analysis was conducted for certain upregulated genes, and the influence of HPCD on protoplasts and single-gene deletion strains was investigated. Six major categories of upregulated genes were identified, including genes associated with the pentose phosphate pathway (oxidative phase), cell wall organization or biogenesis, glutathione metabolism, protein refolding, phosphatidylcholine biosynthesis, and AdoMet synthesis, which are all considered to be associated with cell death induced by HPCD. The inactivation or structure alteration of YNL194Cp in the organelle membrane is considered the critical reason for cell death. We believe this work contributes to elucidating the cell-death mechanism and providing a direction for further research on non-thermal HPCD sterilization technology.

Comparative study of different catalysts mediated FAME conversion from macroalga Padina tetrastromatica biomass and hydrothermal liquefaction facilitated bio-oil production

Marine macroalgae offer an endurable source of renewable biomass, which do not require cultivable area, fertilizers for cultivation for bioproducts production. In this study, marine brown macroalga Padina tetrastromatica as an alternate sustainable feedstock for the production of liquid fuels. Padina tetrastromatica biomass was collected from Mandapam; the coastal region of Rameswaram, Tamil Nadu, India. and the algal oil was extracted using sequential extractions using various solvents. Petroleum ether (PE) and dichloromethane (DCM) solvent fractions were found to have high lipids and further utilized for biodiesel production, wherein four different heterogeneous nanocatalysts (TiO₂, Bio-Fe, GO, and MgO) and commercial homogeneous catalysts (HCl and NaOH) were employed for the transesterification. High fatty acid methyl ester (FAME) recovery (92.3%) was achieved from TiO₂ mediated transesterification than the other conventional catalysts. Further, the conversion of algal biomass into bio-oil and by-products was carried out using hydrothermal liquefaction (HTL). Subsequently, the compounds were characterized by FT-IR and GC-MS analysis. The quality parameters of liquid biofuels were examined and they are in accordance with the international fuel standards. Thus, brown macroalga Padina tetrastromatica may be considered as an alternate feedstock for biofuel and other bioproducts production and TiO₂ would be a suitable catalyst for the conversion of FAME.

Multiplexed proteome profiling of carbon source perturbations in two yeast species with SL-SP3-TMT

Saccharomyces cerevisiae and Schizosaccharomyces pombe are the most commonly studied yeast model systems, yet comparisons of global proteome remodeling between these yeast species are scarce. Here, we profile the proteomes of S. cerevisiae and S. pombe cultured with either glucose or pyruvate as the sole carbon source to define common and distinctive alterations in the protein landscape across species. In addition, we develop an updated streamlined-tandem mass tag (SL-TMT) strategy that substitutes chemical-based precipitation with more versatile bead-based protein aggregation method (SP3) prior to enzymatic digestion and TMT labeling. Our new workflow, SL-SP3-TMT, allow for near-complete proteome profiles in a single experiment for each species. The data reveal expected alterations in protein abundance and differences between species, highlighted complete canonical biochemical pathways, and provided insight into previously uncharacterized proteins. The techniques used herein, namely SL-SP3-TMT, can be applied to virtually any experiment aiming to study remodeling of the proteome using a high-throughput, comprehensive, yet streamlined mass spectrometry-based strategy. SIGNIFICANCE: Saccharomyces cerevisiae and Schizosaccharomyces pombe are single-celled eukaryotes that diverged from a common ancestor over a period of 100 million years, such that evolution has driven fundamental differences between the two species. Cellular metabolism and the regulation thereof are vital for living organisms. Here, we hypothesize that large scale proteomic alterations are prevalent upon the substitution of glucose with another carbon source, in this case pyruvate. To efficiently process our samples, we developed an updated streamlined-tandem mass tag (SL-TMT) strategy with more versatile bead-based protein aggregation. The data revealed expected alterations in protein abundance and illustrated differences between species. We highlighted complete canonical biochemical pathways and provided insight into previously uncharacterized proteins.

Moonlighting Proteins and Cardiopathy in the Spatial Response of MCF-7 Breast Cancer Cells to Tamoxifen

BACKGROUND

The purpose of this study is to apply quantitative high-throughput proteomics methods to investigate dynamic aspects of protein changes in nucleocytoplasmic distribution of proteins and of total protein abundance for MCF-7 cells exposed to tamoxifen (Tam) in order to reveal the agonistic and antagonistic roles of the drug.

EXPERIMENTAL DESIGN

The MS-based global quantitative proteomics with the analysis of fractions enriched in target subcellular locations is applied to measure the changes in total abundance and in the compartmental abundance/distribution between the nucleus and cytoplasm for several thousand proteins differentially expressed in MCF-7 cells in response to Tam stimulation.

RESULTS

The response of MCF-7 cells to the Tam treatment shows significant changes in subcellular abundance rather than in their total abundance. The bioinformatics study reveals the relevance of moonlighting proteins and numerous pathways involved in Tam response of MCF-7 including some of which may explain the agonistic and antagonistic roles of the drug.

CONCLUSIONS

The results indicate possible protective role of Tam against cardiovascular diseases as well as its involvement in G-protein coupled receptors pathways that enhance breast tissue proliferation.

Moonlighting Proteins and Cardiopathy in the Spatial Response of MCF-7 Breast Cancer Cells to Tamoxifen

BACKGROUND

The purpose of this study is to apply quantitative high-throughput proteomics methods to investigate dynamic aspects of protein changes in nucleocytoplasmic distribution of proteins and of total protein abundance for MCF-7 cells exposed to tamoxifen (Tam) in order to reveal the agonistic and antagonistic roles of the drug.

EXPERIMENTAL DESIGN

The MS-based global quantitative proteomics with the analysis of fractions enriched in target subcellular locations is applied to measure the changes in total abundance and in the compartmental abundance/distribution between the nucleus and cytoplasm for several thousand proteins differentially expressed in MCF-7 cells in response to Tam stimulation.

RESULTS

The response of MCF-7 cells to the Tam treatment shows significant changes in subcellular abundance rather than in their total abundance. The bioinformatics study reveals the relevance of moonlighting proteins and numerous pathways involved in Tam response of MCF-7 including some of which may explain the agonistic and antagonistic roles of the drug.

CONCLUSIONS

The results indicate possible protective role of Tam against cardiovascular diseases as well as its involvement in G-protein coupled receptors pathways that enhance breast tissue proliferation.

Data Independent Acquisition Mass Spectrometry Method for Improved Neuropeptidomic Coverage in Crustacean Neural Tissue Extracts

Neuropeptides are an important class of signaling molecules in the nervous and neuroendocrine system, but they are challenging to study due to their low concentration in vivo in the presence of numerous interfering artifacts. Often the limitation of mass spectrometry analyses of neuropeptides in complex tissue extracts is not due to neuropeptides being below the detection limit but due to ions not being selected for tandem mass spectrometry during the liquid chromatography elution time and therefore not being identified. In this study, a data independent acquisition (DIA) method was developed to improve the coverage of neuropeptides in neural tissue from the model organism C. borealis. The optimal mass-to-charge ratio range and isolation window were determined and subsequently used to detect more neuropeptides in extracts from the brain and pericardial organs than the conventional data dependent acquisition method. The DIA method led to the detection of almost twice as many neuropeptides in the brain and approximately 1.5-fold more neuropeptides in the pericardial organs. The technical and biological reproducibility were also explored and found to be improved over the original method, with 56% of neuropeptides detected in 3 out of 3 replicate injections and 62% in 3 out of 3 biological replicates. Furthermore, 68 putative novel neuropeptides were detected and identified with de novo sequencing. The quantitative accuracy of the method was also explored. The developed method is anticipated to be useful for gaining a deeper profiling of neuropeptides, especially those in low abundance, in a variety of sample types.

Characterization of proteome dynamics during growth in oleate reveals a new peroxisome-targeting receptor

To optimally perform the diversity of metabolic functions that occur within peroxisomes, cells must dynamically regulate peroxisome size, number and content in response to the cell state and the environment. Except for transcriptional regulation little is known about the mechanisms used to perform this complicated feat. Focusing on the yeast Saccharomyces cerevisiae, we used complementary high-content screens to follow changes in localization of most proteins during growth in oleate. We found extensive changes in cellular architecture and identified several proteins that colocalized with peroxisomes that had not previously been considered peroxisomal proteins. One of the newly identified peroxisomal proteins, Ymr018w, is a protein with an unknown function that is similar to the yeast and human peroxisomal targeting receptor Pex5. We demonstrate that Ymr018w is a new peroxisomal-targeting receptor that targets a subset of matrix proteins to peroxisomes. We, therefore, renamed Ymr018w, Pex9, and suggest that Pex9 is a condition-specific targeting receptor that enables the dynamic rewiring of peroxisomes in response to metabolic needs. Moreover, we suggest that Pex5-like receptors might also exist in vertebrates.

New Insight Into the Roles of Membrane Microdomains in Physiological Activities of Fungal Cells

The organization of biological membranes into structurally and functionally distinct lateral microdomains is generally accepted. From bacteria to mammals, laterally compartmentalized membranes seem to be a vital attribute of life. The crucial fraction of our current knowledge about the membrane microdomains has been gained from studies on fungi. In this review we summarize the evidence of the microdomain organization of membranes from fungal cells, with accent on their enormous diversity in composition, temporal dynamics, modes of formation, and recognized engagement in the cell physiology. A special emphasis is laid on the fact that in addition to their other biological functions, membrane microdomains also mediate the communication among different membranes within a eukaryotic cell and coordinate their functions. Involvement of fungal membrane microdomains in stress sensing, regulation of lipid homeostasis, and cell differentiation is discussed more in detail.

The interactome challenge

The properties of living cells are mediated by a huge number of ever-changing interactions of their component macromolecules forming living machines; collectively, these are termed the interactome. Pathogenic alterations in interactomes mechanistically underlie diseases. Therefore, there exists an essential need for much better tools to reveal and dissect interactomes. This need is only now beginning to be met.

Redefining the Breast Cancer Exosome Proteome by Tandem Mass Tag Quantitative Proteomics and Multivariate Cluster Analysis

Exosomes are microvesicles of endocytic origin constitutively released by multiple cell types into the extracellular environment. With evidence that exosomes can be detected in the blood of patients with various malignancies, the development of a platform that uses exosomes as a diagnostic tool has been proposed. However, it has been difficult to truly define the exosome proteome due to the challenge of discerning contaminant proteins that may be identified via mass spectrometry using various exosome enrichment strategies. To better define the exosome proteome in breast cancer, we incorporated a combination of Tandem-Mass-Tag (TMT) quantitative proteomics approach and Support Vector Machine (SVM) cluster analysis of three conditioned media derived fractions corresponding to a 10 000g cellular debris pellet, a 100 000g crude exosome pellet, and an Optiprep enriched exosome pellet. The quantitative analysis identified 2 179 proteins in all three fractions, with known exosomal cargo proteins displaying at least a 2-fold enrichment in the exosome fraction based on the TMT protein ratios. Employing SVM cluster analysis allowed for the classification 251 proteins as "true" exosomal cargo proteins. This study provides a robust and vigorous framework for the future development of using exosomes as a potential multiprotein marker phenotyping tool that could be useful in breast cancer diagnosis and monitoring disease progression.

Using data-independent, high-resolution mass spectrometry in protein biomarker research: perspectives and clinical applications

In medicine, there is an urgent need for protein biomarkers in a range of applications that includes diagnostics, disease stratification, and therapeutic decisions. One of the main technologies to address this need is MS, used for protein biomarker discovery and, increasingly, also for protein biomarker validation. Currently, data-dependent analysis (also referred to as shotgun proteomics) and targeted MS, exemplified by SRM, are the most frequently used mass spectrometric methods. Recently developed data-independent acquisition techniques combine the strength of shotgun and targeted proteomics, while avoiding some of the limitations of the respective methods. They provide high-throughput, accurate quantification, and reproducible measurements within a single experimental setup. Here, we describe and review data-independent acquisition strategies and their recent use in clinically oriented studies. In addition, we also provide a detailed guide for the implementation of SWATH-MS (where SWATH is sequential window acquisition of all theoretical mass spectra)-one of the data-independent strategies that have gained wide application of late.

Proteomics reveals the importance of the dynamic redistribution of the subcellular location of proteins in breast cancer cells

At the molecular level, living cells are enormously complicated complex adaptive systems in which intertwined genomic, transcriptomic, proteomic and metabolic networks all play a crucial role. At the same time, cells are spatially heterogeneous systems in which subcellular compartmentalization of different functions is ubiquitous and requires efficient cross-compartmental communication. Dynamic redistribution of multitudinous proteins to different subcellular locations in response to cellular functional state is increasingly recognized as a crucial characteristic of cellular function that seems to be at least as important as overall changes in protein abundance. Characterization of the subcellular spatial dynamics of protein distribution is a major challenge for proteomics and recent results with MCF7 breast cancer cells suggest that this may be of particular importance for cancer cells.

Systems cell biology

Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology.

Multiplexed and data-independent tandem mass spectrometry for global proteome profiling

One of the most important early developments in the field of proteomics was the advent of automated data acquisition routines that allowed high-throughput unattended data acquisition during HPLC introduction of peptide mixtures to a tandem mass spectrometer. Prior to this, data acquisition was orders of magnitude less efficient being based entirely on lists of predetermined ions generated in a prior HPLC-MS experiment. This process, known generically as data-dependent analysis, empowered the development of shotgun proteomics where hundreds to thousands of peptide sequences are matched per experiment. In their most popular implementation, the most abundant ionized species from every precursor ion scan at each moment in chromatographic time are successively selected for isolation, activation and tandem mass analysis. While extremely powerful, this strategy has one primary limitation in that detectable dynamic range is restricted (in a top-down manner) to the peptides that ionize the best. To circumvent the serial nature of the data-dependent process and increase detectable dynamic range, the concepts of multiplexed and data-independent acquisition (DIA) have emerged. Multiplexed-data acquisition is based on more efficient co-selection and co-dissociation of multiple precursor ions in parallel, the data from which is subsequently de-convoluted to provide polypeptide sequences for each individual precursor ion. DIA has similar goals, but there is no real-time ion selection based on prior precursor ion scans. Instead, predefined m/z ranges are interrogated either by fragmenting all ions entering the mass spectrometer at every single point in chromatographic time; or by dividing the m/z range into smaller m/z ranges for isolation and fragmentation. These approaches aim to fully utilize the capabilities of mass spectrometers to maximize tandem MS acquisition time and to address the need to expand the detectable dynamic range, lower the limit of detection, and improve the overall confidence of peptide identifications and relative protein quantification measurements. This review covers all aspects of multiplexed- and data-independent tandem mass spectrometry in proteomics, from experimental implementations to advances in software for data interpretation.

Nuclear cytoplasmic trafficking of proteins is a major response of human fibroblasts to oxidative stress

We have used a subcellular spatial razor approach based on LC-MS/MS-based proteomics with SILAC isotope labeling to determine changes in protein abundances in the nuclear and cytoplasmic compartments of human IMR90 fibroblasts subjected to mild oxidative stress. We show that response to mild tert-butyl hydrogen peroxide treatment includes redistribution between the nucleus and cytoplasm of numerous proteins not previously associated with oxidative stress. The 121 proteins with the most significant changes encompass proteins with known functions in a wide variety of subcellular locations and of cellular functional processes (transcription, signal transduction, autophagy, iron metabolism, TCA cycle, ATP synthesis) and are consistent with functional networks that are spatially dispersed across the cell. Both nuclear respiratory factor 2 and the proline regulatory axis appear to contribute to the cellular metabolic response. Proteins involved in iron metabolism or with iron/heme as a cofactor as well as mitochondrial proteins are prominent in the response. Evidence suggesting that nuclear import/export and vesicle-mediated protein transport contribute to the cellular response was obtained. We suggest that measurements of global changes in total cellular protein abundances need to be complemented with measurements of the dynamic subcellular spatial redistribution of proteins to obtain comprehensive pictures of cellular function.

From proteomes to complexomes in the era of systems biology

Protein complexes carry out almost the entire signaling and functional processes in the cell. The protein complex complement of a cell, and its network of complex-complex interactions, is referred to here as the complexome. Computational methods to predict protein complexes from proteomics data, resulting in network representations of complexomes, have recently being developed. In addition, key advances have been made toward understanding the network and structural organization of complexomes. We review these bioinformatics advances, and their discovery-potential, as well as the merits of integrating proteomics data with emerging methods in systems biology to study protein complex signaling. It is envisioned that improved integration of proteomics and systems biology, incorporating the dynamics of protein complexes in space and time, may lead to more predictive models of cell signaling networks for effective modulation.

The emergence of proteome-wide technologies: systematic analysis of proteins comes of age

During the lifetime of a cell proteins can change their localization, alter their abundance and undergo modifications, all of which cannot be assayed by tracking mRNAs alone. Methods to study proteomes directly are coming of age, thereby opening new perspectives on the role of post-translational regulation in stabilizing the cellular milieu. Proteomics has undergone a revolution, and novel technologies for the systematic analysis of proteins have emerged. These methods can expand our ability to acquire information from single proteins to proteomes, from static to dynamic measures and from the population level to the level of single cells. Such approaches promise that proteomes will soon be studied at a similar level of dynamic resolution as has been the norm for transcriptomes.

Peroxisomes take shape

Peroxisomes carry out various oxidative reactions that are tightly regulated to adapt to the changing needs of the cell and varying external environments. Accordingly, they are remarkably fluid and can change dramatically in abundance, size, shape and content in response to numerous cues. These dynamics are controlled by multiple aspects of peroxisome biogenesis that are coordinately regulated with each other and with other cellular processes. Ongoing studies are deciphering the diverse molecular mechanisms that underlie biogenesis and how they cooperate to dynamically control peroxisome utility. These important challenges should lead to an understanding of peroxisome dynamics that can be capitalized upon for bioengineering and the development of therapies to improve human health.